Decentralized Simultaneous Localization and Mapping (SLAM) faces the problem of exploiting communication. Indirect measurements through the registration of observations are the preferable approach in many scenarios [1]}. Place recognition has emerged as a compact and data-efficient solution [2]}. The work in [3]} uses Vector of Locally Aggregated Descriptors (VLADs) generated by the NetVLAD [4]} to reduce the communication bandwidth. Instead of sending information to all the other agents, the agent sends data only to the robot assigned with a specific descriptor. Although this strategy lowers the used bandwidth, it limits the system's scalability due to the a priori assignment of a centroid of the clusterized feature space. We overcome this problem and generate binary VLADs from the feature descriptors extracted from the frames.
